Zeta: scheduling interactive services with partial execution
Proceedings of the Third ACM Symposium on Cloud Computing
QACO: exploiting partial execution in web servers
Proceedings of the 2013 ACM Cloud and Autonomic Computing Conference
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To service requests with high quality, interactive services such as web search, on-demand video and on line gaming keep average server utilization low. As servers become busy, queuing delays increase, and requests miss their deadlines, resulting in degraded quality of service with poor user experience and potential revenue loss. In this paper, we propose Tians scheduling, a group of scheduling algorithms for interactive services that can produce partial answers during overload. A Tians scheduler allocates processing time to each request based on system load with the objective of maximizing overall quality of responses. We propose three Tians scheduling algorithms--off line, on line clairvoyant and on line non clairvoyant. For interactive applications with concave quality profile, we prove that the off line algorithm is optimal. We show the effectiveness of the on line algorithms by conducting a simulation study modeling important applications--a web search engine and video-on-demand (VOD) system. Simulation results show a significant improvement of Tians over traditional server models: average response quality improves and the variance of responses decreases.